A user has asked for the Study/Indicator version of this Strategy . If you encounter the error "loop....>100ms" simply toggle the eye icon to hide and unhide the indicator The following is simply quoted from my previous post for your convenience: (obviously there won't be risk, Stop Loss, or Take profit parameters!) OPERATING PRINCIPLE The strategy is...
Experiment that uses an (optional) Zero Lag adjustment and KAMA instead of the default SMA to calculate the CCI.
Hi everyone! Introduction A popular use for moving averages is to develop simple trading systems based on moving average crossovers. A trading system using two moving averages would give a buy signal when the shorter (faster) moving average advances above the longer (slower) moving average. A sell signal would be given when the shorter moving average crosses...
Adopted to Pine from www.prorealcode.com . I haven't yet understood the details of the algorithm but it matches the original Jurik's RSX one to one. Jurik's RSX is a "noise free" version of RSI, with no added lag. To learn more about this indicator see www.jurikres.com . Good luck!
Experimental Zero Lag Adjusted KAMA based MACD. Uses Kaufman's Adaptive Moving Average (KAMA) instead of the standard EMAs to calculate the MACD with an optional application of the zero lag adjustment. Significant differences in momentum changes (zero line crossovers), often earlier signal line crossovers and differences in divergences. Chart displays : ...
A derivation of the Kalman Filter. Lower Gain values create smoother results.The ratio Smoothing/Lag is similar to any Low Lagging Filters. The Gain parameter can be decimal numbers. Kalman Smoothing With Gain = 20 For any questions/suggestions feel free to contact me
This script is a crossing of eleven different MA, with alerts and SL and TP. The simplest is what works best. SMA --> Simple EMA --> Exponential WMA --> Weighted VWMA --> Volume Weighted SMMA --> Smoothed DEMA --> Double Exponential TEMA --> Triple Exponential HMA --> Hull TMA --> Triangular SSMA --> SuperSmoother filter ZEMA --> Zero Lag Exponential Using...
An adaptive filtering technique allowing permanent re-evaluation of the filter parameters according to price volatility. The construction of this filter is based on the formula of moving ordinary least squares or lsma , the period parameter is estimated by dividing the true range with its highest. The filter will react faster during high volatility periods and...
Explanation; www.stockspotter.com Açıklama yukarıdaki pdf dosyasında ingilizce olarak mevcuttur.
A study of moving averages that utilizes different tricks I've learned to optimize them. Included is Bollinger Bands, Guppy (GMMA) and Super Guppy. The method used to make it MtF should be more precise and smoother than regular MtF methods that use the security function. For intraday timeframes, each number represents each hour, with 24 equal to 1 day. For daily,...
A quadratic regression is the process of finding the equation that best fits a set of data.This form of regression is mainly used for smoothing data shaped like a parabola. Because we can use short/midterm/longterm periods we can say that we use a Quadratic Least Squares Moving Average or a Moving Quadratic Regression. Like the Linear Regression (LSMA) a...
EN: PRICE SATURATION INDEX is a momentum algorithm that measures price intensity. It helps us to determine the times when the price reaches intensity and calculates the latency in those moving averages. Moving averages have lag. The lag is necessary because the smoothing is done using past data. It shows you how to filtered a selected amount of lag from an...
Single Exponential Smoothing ( ema ) does not excel in following the data when there is a trend. This situation can be improved by the introduction of a second equation with a second constant gamma . The gamma constant cant be lower than 0 and cant be greater than 1, higher values of gamma create less lag while preserving smoothness.Higher values of length ...
Finite Impulse Response (FIR) Filter indicator script. This indicator was originally developed by John F. Ehlers (Stocks & Commodities V. 20:7 (26-31): Zero-Lag Data Smoothers). NOTE: Ehlers' favorite FIR filter had 1, 2, 3, 3, 2, 1, 0 coefficients.
Ahrens Moving Average indicator script. This indicator was originally developed by Richard D. Ahrens (Stocks & Commodities V.31:11 (26-30): Build A Better Moving Average).
Infinite Impulse Response (IIR) Filter indicator script. This indicator was originally developed by John Ehlers (Stocks & Commodities V. 20:7 (26-31): Zero-Lag Data Smoothers).
Zero Lag Exponential Moving Average indicator script based on the original version by John Ehlers and Ric Way